Disentangling the complexity of low complexity proteins

Abstract

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs. Short abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.

ProminTools: shedding light on proteins of unknown function in biomineralization with user friendly tools illustrated using mollusc shell matrix protein sequences

“…Here, using the Sequence Properties Analyzer we were able to demonstrate that this is not a general feature of the data set, which is not predicted to be significantly more disordered than the background proteome. This highlights the importance of the proteome context when assigning significance to protein features, and demonstrates that the generally observed correlation between protein disorder and low complexity ( Mier et al, 2019 ) does not hold in every data set.…”

ProminTools: Shedding light on proteins of unknown function in biomineralization with user friendly tools illustrated using mollusc shell matrix protein sequences

“…Here, using the Sequence Properties Analyzer we were able to demonstrate that this is not a general feature of the data set, which is not predicted to be significantly more disordered than the background proteome. This highlights the importance of the proteome context when assigning significance to protein features, and demonstrates that the generally observed correlation between protein disorder and low complexity [23] does not hold in every data set.…”

Robust Cell-Free Expression of Sub-Pathological and Pathological Huntingtin Exon-1 for NMR Studies. General Approaches for the Isotopic Labeling of Low-Complexity Proteins

“…The investigation of proteins with low-complexity sequences represents a challenge for traditional structural biology approaches [ 27 , 44 ]. Due to their inherent flexibility, NMR is the most suited technique for these studies.…”

“…The optimization of coupling CF expression with the tRNA suppression strategy [ 42 , 43 ], which allows the site-specific isotopic labeling (SSIL) of proteins, is also described. The ensemble of our developments provides new avenues for the structural characterization of proteins hosting low-complexity regions (LCRs) [ 44 ] and, therefore, to decipher the bases of biological processes such as neurodegeneration [ 45 ] or liquid-liquid phase separation [ 46 , 47 ].…”